easyExon – A Java-based GUI tool for processing and visualization of Affymetrix exon array data

<p>Abstract</p> <p>Background</p> <p>Alternative RNA splicing greatly increases proteome diversity and thereby contribute to species- or tissue-specific functions. The possibility to study alternative splicing (AS) events on a genomic scale using splicing-sensitive microarrays, including the Affymetrix GeneChip Exon 1.0 ST microarray (exon array), has appeared very recently. However, the application of this new technology is hindered by the lack of free and user-friendly software devoted to these novel platforms.</p> <p>Results</p> <p>In this study we present a Java-based freeware, easyExon <url>http://microarray.ym.edu.tw/easyexon</url>, to process, filtrate and visualize exon array data with an analysis pipeline. This tool implements the most commonly used probeset summarization methods as well as AS-orientated filtration algorithms, e.g. MIDAS and PAC, for the detection of alternative splicing events. We include a biological filtration function according to GO terms, and provide a module to visualize and interpret the selected exons and transcripts. Furthermore, easyExon can integrate with other related programs, such as Integrate Genome Browser (IGB) and Affymetrix Power Tools (APT), to make the whole analysis more comprehensive. We applied easyExon on a public accessible colon cancer dataset as an example to illustrate the analysis pipeline of this tool.</p> <p>Conclusion</p> <p>EasyExon can efficiently process and analyze the Affymetrix exon array data. The simplicity, flexibility and brevity of easyExon make it a valuable tool for AS event identification in genomic research.</p

A novel strategy for sibship determination in trio sibling model

Aim To use a virtually simulated population, generated from published allele frequencies based on 15 short tandem repeats (STR), to evaluate the efficacy of trio sibship testing and sibling assignment for forensic purposes. Methods Virtual populations were generated using 15 STR loci to create a large number of related and unrelated genotypes (10 000 trio combinations). Using these virtual populations, the probability of related and unrelated profiles can be compared to determine the chance of inclusions of being siblings if they are true siblings and the chance of inclusion if they are unrelated. Two specific relationships were tested – two reference siblings were compared to a third true sibling (3S trio, sibling trio) and two reference siblings were compared to an unrelated individual (2S1U trio, non-sibling trio). Results When the likelihood ratio was greater than 1, 99.87% of siblings in the 3S trio population were considered as siblings (sensitivity); 99.88% of non-siblings in the 2S1U trio population were considered as non-siblings (specificity); 99.9% of both populations were identified correctly as siblings and non-siblings; and the accuracy of the test was 99.88%. Conclusions The high sensitivity and specificity figures when using two known siblings compared to a putative sibling are significantly greater than when using only one known relative. The data also support the use of increasing number of loci allowing for greater confidence in genetic identification. The system established in this study could be used as the model for evaluating and simulating the cases with multiple relatives

The risk of false inclusion of a relative in parentage testing – an in silico population study

Aim To investigate the potential of false inclusion of a close genetic relative in paternity testing by using computer generated families. Methods 10 000 computer-simulated families over three generations were generated based on genotypes using 15 short tandem repeat loci. These data were used in assessing the probability of inclusion or exclusion of paternity when the father is actually a sibling, grandparent, uncle, half sibling, cousin, or a random male. Further, we considered a duo case where the mother’s DNA type was not available and a trio case including the mother’s profile. Results The data showed that the duo scenario had the highest and lowest false inclusion rates when considering a sibling (19.03 ± 0.77%) and a cousin (0.51 ± 0.14%) as the father, respectively; and the rate when considering a random male was much lower (0.04 ± 0.04%). The situation altered slightly with a trio case where the highest rate (0.56 ± 0.15%) occurred when a paternal uncle was considered as the father, and the lowest rate (0.03 ± 0.03%) occurred when a cousin was considered as the father. We also report on the distribution of the numbers for non-conformity (non-matching loci) where the father is a close genetic relative. Conclusions The results highlight the risk of false inclusion in parentage testing. These data provide a valuable reference when incorporating either a mutation in the father’s DNA type or if a close relative is included as being the father; particularly when there are varying numbers of non-matching loci

A novel strategy for sibship determination in trio sibling model

Aim To use a virtually simulated population, generated from published allele frequencies based on 15 short tandem repeats (STR), to evaluate the efficacy of trio sibship testing and sibling assignment for forensic purposes. Methods Virtual populations were generated using 15 STR loci to create a large number of related and unrelated genotypes (10 000 trio combinations). Using these virtual populations, the probability of related and unrelated profiles can be compared to determine the chance of inclusions of being siblings if they are true siblings and the chance of inclusion if they are unrelated. Two specific relationships were tested – two reference siblings were compared to a third true sibling (3S trio, sibling trio) and two reference siblings were compared to an unrelated individual (2S1U trio, non-sibling trio). Results When the likelihood ratio was greater than 1, 99.87% of siblings in the 3S trio population were considered as siblings (sensitivity); 99.88% of non-siblings in the 2S1U trio population were considered as non-siblings (specificity); 99.9% of both populations were identified correctly as siblings and non-siblings; and the accuracy of the test was 99.88%. Conclusions The high sensitivity and specificity figures when using two known siblings compared to a putative sibling are significantly greater than when using only one known relative. The data also support the use of increasing number of loci allowing for greater confidence in genetic identification. The system established in this study could be used as the model for evaluating and simulating the cases with multiple relatives

The incidence and risk of developing a second primary esophageal cancer in patients with oral and pharyngeal carcinoma: a population-based study in Taiwan over a 25 year period

<p>Abstract</p> <p>Background</p> <p>The incidence of oral and pharyngeal (including oral cavity, oropharynx and hypopharynx) carcinoma increases rapidly in Asia and South Pacific because of betel quid chewing. Thus far, large-scale epidemiological studies are not available yet to stratify these patients by their risks of developing a second primary cancer in the digestive tract including esophagus, stomach, colon, and rectum.</p> <p>Methods</p> <p>A population-based study was conducted using the database from the Taiwan National Cancer Registry for the period 1979-2003. We quantified standardized incidence ratios (SIRs) and cumulative incidence of second primary cancers among 33,787 patients with initial diagnoses of oral and pharyngeal carcinoma.</p> <p>Results</p> <p>Among these four digestive tract organs, the esophagus was the only site of second cancer with excess risk in patients with oral and pharyngeal carcinoma. The incidence and risk of developing a second primary esophageal cancer differed by the site of the primary index tumor, most frequently seen in hypopharyngeal cancer (71/4,218 = 1.68%, SIR = 22.76, 95% CI 17.77-28.70), followed by oropharyngeal cancer (30/3,403 = 0.88%, SIR = 14.29, 95% CI 9.64-20.39) and the least in oral cavity cancer (99/26,166 = 0.38%, SIR = 5.57, 95% CI 4.53-6.78). In addition, the risk was extraordinarily high for patients with a follow-up interval ≤ 1 year and those with first primary cancer diagnosed at age ≤50. These patients may justify more close surveillance.</p> <p>Conclusion</p> <p>The present study represents the first population-based study in Asia attempting to stratify the patients of oral and pharyngeal carcinoma by their risk of developing a second esophageal cancer. It helps identify patients at high risk and tailor the application of intense follow-up surveillance to the estimated risk in each individual case.</p